- Prediction candidate presentation
- Operation and Control
- Operation plan
- Sensor data recognition
- Status estimation
- Media recognition
Predicting other vehicles’ behavior
Predicts future risks, to enable saver, smoother automatic driving.
- Predicts the position and trajectory of the other vehicle a few seconds ahead, based on the shape of the intersection and lane information.
- Detects locations where pedestrians might suddenly appear from a blind spot, using only the vehicle’s onboard sensors.
- Strategic decision making in automatic driving based on risk prediction
- Automatic brakes and other Advanced Driver-Assistance Systems (ADAS)
- Vehicle-to-infrastructure (V2I) communications; e.g., notification of vehicles that present potential risks
- Route planning for transport robots that do not interfere with workers in logistics warehouses
- Other cases of mobile robot control requiring attention to moving objects nearby
Benchmarks, strengths, and track record
- Can be applied to intersections with any shapes, to enable simultaneous predictions of which lane will be used when multiple lanes are available.
- Predicts behavior on any place without preparing high-precision maps in advance.
- Predicts the shape of roads and obstacles using multiple candidates, where blind spots prevent narrowing down to a single candidate.
- Accepted by top international conferences on robots and image processing.
- International Conference on Robotics and Automation (ICRA) 2020
- Intelligent Transportation Systems Conference (ITSC) 2019
- Intelligent Vehicles Symposium (IV) 2018
- Winter Conference on Applications of Computer Vision (WACV) 2021
Please include the title “Toshiba AI Technology Catalog: Predicting other vehicles’ behavior” or the URL in the inquiry text.
Please note that because this technology is currently the subject of R&D activities, immediate responses to inquiries may not be possible.
- A. Kawasaki and A. Seki, "Multimodal Trajectory Predictions for Urban Environments Using Geometric Relationship between a Vehicle and Lanes,” ICRA, 2020.
- T. Sugiura and T. Watanabe, “Probable Multi-hypothesis Blind Spot Estimation for Driving Risk Prediction,” ITSC, 2019.
- A. Kawasaki and T. Tasaki, “Trajectory Prediction of Turning Vehicles based on Intersection Geometry and Observed Velocities,” IV, 2018.
- A. Kawasaki and A. Seki, "Multimodal Trajectory Predictions for Autonomous Driving Without a Detailed Prior Map,” WACV, 2021.